def _annotate(self, root, weights={}):
'''Actually annotates d-DNNF with weights'''
if(str(root.label)[0] == 'A'):
root.weight = mpq('1')
for ch in root.children: #can perform IBCP for conditioning
root.weight *= self._annotate(ch, weights=weights)
return root.weight
elif(str(root.label)[0] == 'O'):
root.weight = self._annotate(root.children[0], weights=weights) + self._annotate(root.children[1], weights=weights)
return root.weight
else:
try:
int(root.label)
if weights and abs(int(root.label)) in weights:
if int(root.label) > 0:
root.weight = weights[int(root.label)]
else:
root.weight = mpq('1')-weights[abs(int(root.label))]
else:
root.weight = mpq('0.5')
except:
if (str(root.label)[0] == 'F'):
root.weight = 0
elif (str(root.label)[0] == 'T'):
root.weight = 1
return root.weight
def f_lkFiqn(l, k, i, n):
'''
This function computes the values of the easy basis f_lk(F_i (q_n))
(level 1 of SG) based on the Splines on Fractals paper.
Args:
l, k, i, n: correspond to the indices mentioned in the preceding
paragraph.
Returns:
values of the easy basis f_lk(F_i (q_n))
'''
# Finds the values of pi and qi from the recursion
arr = big_recursion(l)
p1 = copy.deepcopy(arr[2, l])
q1 = copy.deepcopy(arr[3, l])
# Find the values of easy basis from (5.2) of splines paper
if i == n and i == k:
return int(l == 0)
if i == k and i != n:
return gm.mpq(p1, (5**l))
if i == n and i != k:
return 0
if k == n and k != i:
return gm.mpq(p1, (5**l))
return gm.mpq(q1, (5**l))
def annotate(self,root, weights = None):
'''Computes Model Counts'''
if(str(root.label)[0] == 'A'):
root.weight = mpq('1')
for ch in root.children: #can perform IBCP for conditioning
root.weight *= self.annotate(ch, weights=weights)
return root.weight
elif(str(root.label)[0] == 'O'):
root.weight = self.annotate(root.children[0], weights=weights) + self.annotate(root.children[1], weights=weights)
return root.weight
else:
try:
int(root.label)
if weights and abs(int(root.label)) in weights:
if int(root.label) > 0:
root.weight = weights[int(root.label)]
else:
root.weight = mpq('1')-weights[abs(int(root.label))]
else:
root.weight = mpq('0.5')
except:
if (str(root.label)[0] == 'F'):
root.weight = 0
elif (str(root.label)[0] == 'T'):
root.weight = 1
return root.weight
def __mul__(lhs,rhs):
if isinstance(rhs,(Number,type(mpz(0)),type(mpq(0,1)))):
ret = DPolynomial(lhs.Nvar , lhs.Nweight , lhs.weightMat)
if rhs==0:return ret
for (m,c) in lhs.coeffs.items():
ret.coeffs[m] = c*rhs
ret.weights[m] = lhs.weights[m]
ret._normalized = False
return ret
elif isinstance(lhs,(Number,type(mpz(0)),type(mpq(0,1)))):
ret = DPolynomial(rhs.Nvar , rhs.Nweight , rhs.weightMat)
if lhs==0:return ret
for (m,c) in rhs.coeffs.items():
ret.coeffs[m] = c*lhs
ret.weights[m] = rhs.weights[m]
ret._normalized = False
return ret
else:
ret = DPolynomial(lhs.Nvar , lhs.Nweight , lhs.weightMat)
for (m1,c1) in lhs.coeffs.items():
if c1==0:continue
for (m2,c2) in rhs.coeffs.items():
if c2==0:continue
m3 = iadd(m1,m2)
ret.coeffs[m3] = ret.coeffs.get(m3,0) + (c1*c2)
ret.weights[m3] = iadd(lhs.weights[m1] , rhs.weights[m2])
return ret.normalize()
def calculate_babai_optimal_basis():
"""
Calculate the Babai optimal basis for the zero decomposition lattice L (see Definition 1 of the FourQ paper).
:return: B = [b1, b2, b3, b4]
"""
# Note that int(V/r) will give the wrong result, the same applies to math.floor() and round()
alpha = V // r # due to V = 0 mod r, which gives alpha = V /r \in Z
b1 = [
16 * (-60 * alpha + 13 * r - 10), 4 * (-10 * alpha - 3 * r + 12),
4 * (-15 * alpha + 5 * r - 13), -13 * alpha - 6 * r + 3
]
b2 = [32 * (5 * alpha - r), -8, 8, 2 * alpha + r]
b3 = [
16 * (80 * alpha - 15 * r + 18), 4 * (18 * alpha - 3 * r - 16),
4 * (-15 * alpha - 9 * r + 15), 15 * alpha + 8 * r + 3
]
b4 = [
16 * (-360 * alpha + 77 * r + 42), 4 * (42 * alpha + 17 * r + 72),
4 * (85 * alpha - 21 * r - 77), (-77 * alpha - 36 * r - 17)
]
b1 = list(map(lambda x: mpq(x, 224), b1))
b2 = list(map(lambda x: mpq(x, 8), b2))
b3 = list(map(lambda x: mpq(x, 224), b3))
b4 = list(map(lambda x: mpq(x, 448), b4))
result = [b1, b2, b3, b4]
# Compare with expected results (taken from curve4Q on Github)
expected_results = [basis1, basis2, basis3, basis4]
for bi, exp_bi in zip(result, expected_results):
for bij, exp_bij in zip(bi, exp_bi):
assert int(bij) == exp_bij
return result
def beta_array(max_order):
'''
Calculates the array of beta_j up to some order
Args:
max_order: Maximum order of j to be calculated (should be >= 1)
Returns:
beta_arr: np.array of length (max_order+1) containing the first
values of beta up to beta_{max_order}.
'''
# alpha's are used in the calculation of beta, so we first calculate
# these
alpha_arr = alpha_array(max_order+2)
# initialize values of beta_arr
beta_arr = zeros_gm(max_order + 1, 1)
beta_arr[0] = gm.mpq(-1,2)
for j in range(1, max_order+1):
for l in range(j):
beta_arr[j] = beta_arr[j] + (3 * (5 ** (j-l)) -
5 ** (l + 1) + 6) * alpha_arr[j-l] * beta_arr[l]
beta_arr[j] = beta_arr[j] * gm.mpq(2 , (15 * (5 ** j - 1)))
return beta_arr[:, 0]
def prob(squares, initial_pos):
rbound = len(squares) - 1
max_step = len(SEQUENCE) - 1
q = collections.deque()
q.append((0, initial_pos, mpq(1)))
total_prob = mpq(0)
while q:
step, pos, p = q.popleft()
if (squares[pos] and SEQUENCE[step] == "P") or (
not squares[pos] and SEQUENCE[step] == "N"
):
p *= mpq(2, 3)
else:
p *= mpq(1, 3)
if step == max_step:
total_prob += p
continue
step += 1
if pos == 0:
q.append((step, 1, p))
elif pos == rbound:
q.append((step, pos - 1, p))
else:
p *= mpq(1, 2)
q.append((step, pos + 1, p))
q.append((step, pos - 1, p))
return total_prob
def square(x, n):
k = 1
while k > 0:
y = gmpy2.sqrt((mpq(x) + mpq(k))**2 - mpq(n))
if gmpy2.is_integer(y):
return y, k
else:
k += 1
def __lp_av_score_fct(i, l):
# l-th root of i
# l=1 ... Approval Voting
# l=\infty ... Chamberlin-Courant
if i == 1:
return 1
else:
return i**mpq(1, l) - (i - 1)**mpq(1, l)
def test_default_time_from_fraction(self):
# assert mocking did no permanent damage
self.assertIs(gmpy2.mpq, qutypes.TimeType)
t = qutypes.time_from_fraction(43, 12)
# your challenge: find a better way
mpq_type = type(gmpy2.mpq())
self.assertIsInstance(t, mpq_type)
self.assertEqual(t, gmpy2.mpq(43, 12))
def find_d(totient, coprime):
k = 1
k = mpq(k)
d = 2.9
d = mpq(d)
while d % 1 != 0:
d = ((k * totient) + 1) / coprime
k += 1
return d
def test_default_time_from_float(self):
# assert mocking did no permanent damage
self.assertIs(gmpy2.mpq, qutypes.TimeType)
self.assertEqual(qutypes.time_from_float(123 / 931),
gmpy2.mpq(123, 931))
self.assertEqual(qutypes.time_from_float(1000000 / 1000001, 1e-5),
gmpy2.mpq(1))
def cf2f(cf):
'''
Continued fraction to fraction
'''
f = g.mpq(0,1)
for x in reversed(cf):
try:
f = 1 / (f+x)
except ZeroDivisionError:
return g.mpq(0, 1)
return 1/f
def allPrimesDevergesSum():
from Primes import Primes
p = Primes()
primeList = p.getPrimesList(2,10000000)
import gmpy2
pInv = gmpy2.mpq(0,1)
for prime in primeList:
pInv += gmpy2.mpq(1, prime)
m = gmpy2.mpfr(pInv)
print("On prime ", prime, " summ is ", str(m))
if m > 3:
break
def normalizeWeights(weights):
'''
Normalizes the weights
Assumes that either weights defines all positive literal weights between 0 and 1 or
defines weights for both positive and negative literals.
'''
for key in weights:
if -1*key in weights:
if key>0:
weights[key] = mpq(Fraction(weights[key]))/(mpq(Fraction(weights[key])) + mpq(Fraction(weights[key*-1])))
del weights[-1*key]
else:
weights[-1*key] = mpq(Fraction(-1*key))/(mpq(Fraction(weights[key])) + mpq(Fraction(weights[key*-1])))
del weights[key]
def main():
T_distribution = {i: mpq(1, 4) for i in range(1, 5)}
C_distribution = calculate_sum_distribution(6, T_distribution)
O_distribution = calculate_sum_distribution(8, C_distribution)
D_distribution = calculate_sum_distribution(12, O_distribution)
var = float(calculate_sum_variance(20, D_distribution))
print(f"{var:.4f}")
def _get_seq_of_edges_to_add(avg_deg):
aux = gm.mpq(avg_deg)
seq_len = int(min(aux.numerator, aux.denominator))
seq_val = int(max(aux.numerator, aux.denominator) / seq_len)
edges_seq = [seq_val for i in range(seq_len)]
edges_seq[0] += 1
return edges_seq
def solve(groups):
times = []
for D, H, M in groups:
arrival = M * gmpy2.mpq(360-D, 360)
period = M
times.append((arrival, period))
times.sort()
if len(times) <= 1:
return 0
# print(times)
min_encounters = float('inf')
for i, (arrival, period) in enumerate(times):
# print(arrival, period)
num_encounters = 0
for j, (a, p) in enumerate(times):
if i == j:
continue
if a > arrival:
num_encounters += 1
else:
tm = (arrival - a) / p
# print(a, p, "=>", tm)
q, r = gmpy2.f_divmod(tm.numerator, tm.denominator)
num_encounters += q
if r == 0:
# If they're slower and arrive at the same time,
# we don't encounter them.
if p > period:
num_encounters -= 1
# print("encounters:", num_encounters)
if num_encounters < min_encounters:
min_encounters = num_encounters
return min_encounters
def test_is_methods(self):
self.assertFalse(is_pysmt_fraction(4))
self.assertTrue(is_pysmt_fraction(Fraction(4)))
self.assertFalse(is_pysmt_integer(4.0))
self.assertTrue(is_pysmt_integer(Integer(4)))
self.assertTrue(is_python_integer(int(2)))
if PY2:
self.assertTrue(is_python_integer(long(2)))
if HAS_GMPY:
from gmpy2 import mpz
self.assertTrue(is_python_integer(mpz(1)))
if HAS_GMPY:
from gmpy2 import mpz, mpq
self.assertTrue(is_python_rational(mpz(1)))
self.assertTrue(is_python_rational(mpq(1)))
if PY2:
self.assertTrue(is_python_rational(long(1)))
self.assertTrue(is_python_rational(pyFraction(5)))
self.assertTrue(is_python_rational(3))
self.assertTrue(is_python_boolean(True))
self.assertTrue(is_python_boolean(False))
def test_parse():
A, m, d = reader('data/arrangement.ine')
assert m == 4
assert d == 3
A1 = [[3, -1, -1], [-1, 1, 0], [-1, 0, 1], [3, -2, 0]]
A1 = [[mpq(a) for a in ai] for ai in A1]
assert A == A1
def fetchWeights(weightFile):
'''either specify all positive literal weights between 0 and 1 or
specify weights for both positive and negative literals.'''
data = open(weightFile).read()
lines = data.strip().split("\n")
weights = {}
for line in lines:
if int(line.split(',')[0])*(-1) in weights:
if int(line.split(',')[0]) > 0:
weights[int(line.split(',')[0])] = mpq(Fraction(line.split(',')[1]))/(weights.pop(int(line.split(',')[0])*(-1), None)+mpq(Fraction(line.split(',')[1])))
else:
weights[int(line.split(',')[0])*(-1)] = weights[int(line.split(',')[0])*(-1)]/(weights[int(line.split(',')[0])*(-1)]+mpq(Fraction(line.split(',')[1])))
else:
weights[int(line.split(',')[0])] = mpq(Fraction(line.split(',')[1]))
#print(weights)
return weights
def test_real(self):
"""Create Real using different constant types."""
from fractions import Fraction as pyFraction
from pysmt.constants import HAS_GMPY
v1 = (1, 2)
v2 = 0.5
v3 = pyFraction(1, 2)
v4 = Fraction(1, 2)
c1 = self.mgr.Real(v1)
c2 = self.mgr.Real(v2)
c3 = self.mgr.Real(v3)
c4 = self.mgr.Real(v4)
self.assertIs(c1, c2)
self.assertIs(c2, c3)
self.assertIs(c3, c4)
if HAS_GMPY:
from gmpy2 import mpq, mpz
v5 = (mpz(1), mpz(2))
v6 = mpq(1, 2)
c5 = self.mgr.Real(v5)
c6 = self.mgr.Real(v6)
self.assertIs(c4, c5)
self.assertIs(c5, c6)
def _smt_query(self, s, constraints):
self.stats.smt += 1
if not self.cvc4: # Use z3
if s.check() == z3.sat:
self.stats.sat += 1
# Build and return a Solution instance
hole_values = self.holes_from_model(s.model())
soln = self.sketch.partial_evaluate(*hole_values)
# Make sure the synthesized program is consistent with constraints
self.sanity_check(soln, constraints)
return SMTSolution(prog=soln, holes=hole_values)
else: # unsat
self.stats.unsat += 1
self.extract_unsat_core(s.unsat_core(), constraints)
return None
else: # Use cvc4
model,core = cvc4_query_from_z3(s, list(self.Holes._fields), ['p' + str(i) for i in range(len(constraints))])
if model is not None: # sat
assert core is None
self.stats.sat += 1
hole_values = self.Holes(**{attr : mpq(*model[attr]) for attr in model})
soln = self.sketch.partial_evaluate(*hole_values)
# Make sure the synthesized program is consistent with constraints
self.sanity_check(soln, constraints)
return SMTSolution(prog=soln, holes=hole_values)
elif core is not None: # unsat
assert model is None
self.stats.unsat += 1
self.extract_unsat_core(core, constraints)
return None
else:
assert False
def test_is_methods(self):
from fractions import Fraction as pyFraction
self.assertFalse(is_pysmt_fraction(4))
self.assertTrue(is_pysmt_fraction(Fraction(4)))
self.assertFalse(is_pysmt_integer(4.0))
self.assertTrue(is_pysmt_integer(Integer(4)))
self.assertTrue(is_python_integer(int(2)))
if PY2:
self.assertTrue(is_python_integer(long(2)))
if HAS_GMPY:
from gmpy2 import mpz
self.assertTrue(is_python_integer(mpz(1)))
if HAS_GMPY:
from gmpy2 import mpz, mpq
self.assertTrue(is_python_rational(mpz(1)))
self.assertTrue(is_python_rational(mpq(1)))
if PY2:
self.assertTrue(is_python_rational(long(1)))
self.assertTrue(is_python_rational(pyFraction(5)))
self.assertTrue(is_python_rational(3))
self.assertTrue(is_python_boolean(True))
self.assertTrue(is_python_boolean(False))
def test_real(self):
"""Create Real using different constant types."""
from fractions import Fraction as pyFraction
from pysmt.constants import HAS_GMPY
v1 = (1,2)
v2 = 0.5
v3 = pyFraction(1,2)
v4 = Fraction(1,2)
c1 = self.mgr.Real(v1)
c2 = self.mgr.Real(v2)
c3 = self.mgr.Real(v3)
c4 = self.mgr.Real(v4)
self.assertIs(c1, c2)
self.assertIs(c2, c3)
self.assertIs(c3, c4)
if HAS_GMPY:
from gmpy2 import mpq, mpz
v5 = (mpz(1), mpz(2))
v6 = mpq(1,2)
c5 = self.mgr.Real(v5)
c6 = self.mgr.Real(v6)
self.assertIs(c4, c5)
self.assertIs(c5, c6)
def tau_array(max_order):
'''
Calculates the array of tau_j up to some order (this is
originally called t in the Calculus paper)
Args:
max_order: Maximum order of j to be calculated (should be >= 1)
Returns:
tau_arr: np.array of length (max_order+1) containing the first
values of tau up to tau_{max_order}.
'''
tau_arr = zeros_gm(max_order + 1, 1)
tau_arr[0] = gm.mpq(-1, 2)
alpha_arr = alpha_array(max_order+1)
beta_arr = beta_array(max_order)
for j in range(1, max_order + 1):
res = beta_arr[j]
for l in range(j):
res -= 6*alpha_arr[j+1-l]*tau_arr[l]
tau_arr[j] = res
return tau_arr
def make_hilbert(dim=5):
return [
[
gmpy2.mpq(1, i+j+1)
for j in range(dim)
]
for i in range(dim)
]
def ReKeyGen(self, PP, sk_s, pk_b):
g_k = PP['g_k']
k = self.k
g_tk = pk_b**k
g_sk = g_k**sk_s
rk_sb = gmpy2.mpq(g_tk, g_sk)
return rk_sb
def find_phi(N):
factors = factorize(N)
if factors is None:
return None
phi = gmpy2.mpq(N)
for f in factors:
phi = phi * (1 - 1 / f[0])
return phi
def to_python(self, value):
if value is None:
return value
try:
return mpq(value)
except (TypeError, ValueError):
msg = self.error_messages['invalid'] % str(value)
raise exceptions.ValidationError(msg)
def _convergent(coeffs):
"""Compute the convergent of 'coeffs'."""
f = gmpy2.mpq(0, 1)
for x in reversed(coeffs):
try:
f = 1 / (f + x)
except ZeroDivisionError:
return f
return 1 / f
def test_sympify_gmpy():
if HAS_GMPY:
import gmpy2 as gmpy
value = sympify(gmpy.mpz(1000001))
assert value == Integer(1000001) and type(value) is Integer
value = sympify(gmpy.mpq(101, 127))
assert value == Rational(101, 127) and type(value) is Rational
def test_sympify_gmpy():
if HAS_GMPY:
import gmpy2 as gmpy
value = sympify(gmpy.mpz(1000001))
assert value == Integer(1000001) and type(value) is Integer
value = sympify(gmpy.mpq(101, 127))
assert value == Rational(101, 127) and type(value) is Rational
def pi():
# https://web.archive.org/web/20150627225748/http://en.literateprograms.org/Pi_with_the_BBP_formula_%28Python%29
x = 0
n = 1
while 1:
p = mpq((120 * n - 89) * n + 16,
(((512 * n - 1024) * n + 712) * n - 206) * n + 21)
x = mod1(16 * x + p)
n += 1
yield int(16 * x)
def norm_f_jk(addr, j, k):
'''
This function calculates the value of the normal derivative of the
easy basis partial_{n}f_jk at a point on SG addressed by addr.
Args:
j, k: indices mentioned in preceding paragraph.
addr: address of evaluation point F_w(q_n) given as a string of
digits whose first digit is i and whose following digits are
those in w.
Returns:
value of partial_{n}f_jk(F_w(q_n))
'''
# Finds the values of pi and qi from the recursion
arr = big_recursion(j)
a1 = copy.deepcopy(arr[0, j - 1])
b1 = copy.deepcopy(arr[1, j - 1])
# Base case: partial_{n}f_jk(q_i)
if len(addr) == 1:
if (j == 0) and (int(addr[0]) == k):
return 2
elif (j == 0) and (int(addr[0]) != k):
return -1
elif (j != 0) and (int(addr[0]) == k):
return a1
else:
return b1
# Inductive case
last = int(addr[-1])
addr = addr[:-1]
outer_sum = 0
for l in range(j + 1):
inner_sum = 0
for n in range(3):
inner_sum += f_lkFiqn(j - l, k, last, n) * norm_f_jk(addr, l, n)
inner_sum *= (gm.mpq(1, 5))**l
outer_sum += inner_sum
outer_sum *= gm.mpq(5, 3)
return outer_sum
def annotate(self,root, weights = None, maximum=False, minimum=False):
'''Computes Model Counts'''
if(str(root.label)[0] == 'A'):
root.weight = mpq('1')
for ch in root.children: #can perform IBCP for conditioning
root.weight *= self.annotate(ch, weights=weights, maximum=maximum, minimum=minimum)
return root.weight
elif(str(root.label)[0] == 'O'):
self.annotate(root.children[0], weights=weights, maximum=maximum, minimum=minimum)
self.annotate(root.children[1], weights=weights, maximum=maximum, minimum=minimum)
if (maximum and root.children[0].weight >= root.children[1].weight):
print("Hey")
root.weight = root.children[0].weight
root.children[1].weight = 0 #This will help in sampling
elif (maximum and root.children[0].weight < root.children[1].weight):
root.weight = root.children[1].weight
root.children[0].weight = 0 #This will help in sampling
elif (minimum and root.children[0].weight <= root.children[1].weight):
root.weight = root.children[0].weight
root.children[1].weight = 0 #This will help in sampling
elif (minimum and root.children[0].weight > root.children[1].weight):
root.weight = root.children[1].weight
root.children[0].weight = 0 #This will help in sampling
else: #This is normal case
root.weight = root.children[0].weight + root.children[1].weight
return root.weight
else:
try:
int(root.label)
if weights and abs(int(root.label)) in weights:
if int(root.label) > 0:
root.weight = weights[int(root.label)]
else:
root.weight = mpq('1')-weights[abs(int(root.label))]
else:
root.weight = mpq('0.5')
except:
if (str(root.label)[0] == 'F'):
root.weight = 0
elif (str(root.label)[0] == 'T'):
root.weight = 1
return root.weight
def __sub__(lhs,rhs):
ret = DExpression(lhs.Nvar)
ret.coeffs = copy.deepcopy(lhs.coeffs)
if isinstance(rhs,DExpression):
assert(lhs.Nvar==rhs.Nvar)
for (m,c) in rhs.coeffs.items():
ret.coeffs[m] = ret.coeffs.get(m,0)-c
elif isinstance(rhs,(Number,type(mpz(0)),type(mpq(0,1)))):
ret.coeffs[0] -= rhs
ret._simplified = lhs._simplified
return ret.simplify()
def __eq__(lhs,rhs):
if isinstance(rhs,DExpression):
lhs.simplify()
rhs.simplify()
if len(lhs.coeffs)!=len(rhs.coeffs):return False
for (m,c) in lhs.coeffs.items():
if not m in rhs.coeffs or rhs.coeffs[m]!=c:return False
return True
elif isinstance(rhs,(Number,type(mpz(0)),type(mpq(0,1)))):
return (list(lhs.coeffs.keys())==[0] and lhs.coeffs[0]==rhs)
else:
return False
def __add__(lhs , rhs):
ret = copy.deepcopy(lhs)
ret._normalized = False
if isinstance(rhs,(Number,type(mpz(0)),type(mpq(0,1)))):
m = tuple([0]*lhs.Nvar)
ret.coeffs[m] = ret.coeffs.get(m,0)+rhs
ret.weights[m] = tuple([0]*lhs.Nweight)
elif isinstance(rhs,DPolynomial):
for (m,c) in rhs.coeffs.items():
ret.coeffs[m] = ret.coeffs.get(m,0)+c
ret.weights[m] = rhs.weights[m]
return ret.normalize()
def __mul__(lhs,rhs):
ret = DExpression(lhs.Nvar)
if isinstance(rhs,DExpression):
assert(lhs.Nvar==rhs.Nvar)
for (m1,c1) in lhs.coeffs.items():
for (m2,c2) in rhs.coeffs.items():
c3 = c1*c2
m3 = im_mul(m1 , m2 , ret.Nvar)
ret.coeffs[m3] = ret.coeffs.get(m3,0)+c3
elif isinstance(rhs,(Number,type(mpz(0)),type(mpq(0,1)))):
for m1 in lhs.coeffs.keys():
ret.coeffs[m1] = lhs.coeffs[m1]*rhs
return ret.simplify()
def __eq__(lhs , rhs):
lhs.normalize()
if isinstance(rhs,DPolynomial):
rhs.normalize()
if len(lhs.coeffs)!=len(rhs.coeffs):return False
if lhs.Nvar!=rhs.Nvar:return False
for m,c in lhs.coeffs.items():
if c!=rhs.coeffs.get(m,0):return False
return True
elif isinstance(rhs,(Number,type(mpz(0)),type(mpq(0,1)))):
if len(lhs.coeffs)>1:
return False
if len(lhs.coeffs)==0:return (rhs==0)
m,c = list(lhs.coeffs.items())[0]
if c==rhs and all([x==0 for x in m]):return True
return False
# partial unit test for gmpy2 mpq functionality
# relies on Tim Peters' "doctest.py" test-driver
r'''
>>> dir(a)
['__abs__', '__add__', '__bool__', '__class__', '__delattr__', '__divmod__', '__doc__', '__eq__', '__float__', '__floordiv__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__int__', '__le__', '__lt__', '__mod__', '__mul__', '__ne__', '__neg__', '__new__', '__pos__', '__pow__', '__radd__', '__rdivmod__', '__reduce__', '__reduce_ex__', '__repr__', '__rfloordiv__', '__rmod__', '__rmul__', '__rpow__', '__rsub__', '__rtruediv__', '__setattr__', '__sizeof__', '__str__', '__sub__', '__subclasshook__', '__truediv__', 'binary', 'denominator', 'digits', 'numerator']
>>>
'''
import gmpy2 as _g, doctest,sys
import fractions
F=fractions.Fraction
__test__={}
a=_g.mpq('123/456')
b=_g.mpq('789/123')
af=F(123,456)
bf=F(789,123)
__test__['compat']=\
r'''
>>> a==af
True
>>> af==a
True
>>> a < af
False
>>> a <= af
True
>>> a > af
False
>>> a >= af
def test_dup_ff_div_gmpy2():
try:
from gmpy2 import mpq
except ImportError:
return
from sympy.polys.domains import GMPYRationalField
K = GMPYRationalField()
f = [mpq(1,3), mpq(3,2)]
g = [mpq(2,1)]
assert dmp_ff_div(f, g, 0, K) == ([mpq(1,6), mpq(3,4)], [])
f = [mpq(1,2), mpq(1,3), mpq(1,4), mpq(1,5)]
g = [mpq(-1,1), mpq(1,1), mpq(-1,1)]
assert dmp_ff_div(f, g, 0, K) == ([mpq(-1,2), mpq(-5,6)], [mpq(7,12), mpq(-19,30)])
import gmpy2
import fractions
import sys
try:
m = sys.hash_info.modulus
except NameError:
print("new-style hash is not supported")
sys.exit(0)
for s in [0, m//2, m, m*2, m*m, 7, 13, 19, 87907, 79797, 44*44]:
for i in range(-10,10):
for k in [-1, 1, 7, 11, -(2**15), 2**16, 2**30, 2**31, 2**32, 2**33, 2**61, -(2**62), 2**63, 2**64]:
val = k*(s + i)
assert hash(val) == hash(gmpy2.mpz(val)), (val, hash(val), hash(gmpy2.mpz(val)))
print("hash tests for integer values passed")
for d in [1, -2, 3, -47, m, m*2, 324, 797080, -979]:
for s in [0, m//2, m, m*2, m*m]:
for i in range(-10,10):
for k in [-1, 1, 7, 11, -(2**15), 2**16, 2**30, 2**31, 2**32, 2**33, 2**61, -(2**62), 2**63, 2**64, 131313164, -4643131646131346460964347]:
val = k*(s + i)
if val:
assert hash(fractions.Fraction(d,val)) == hash(gmpy2.mpq(d,val)), (d,val,hash(fractions.Fraction(d,val)),hash(gmpy.mpq(d,val)))
if d:
assert hash(fractions.Fraction(val,d)) == hash(gmpy2.mpq(val,d)), (val,d,hash(fractions.Fraction(val,d)),hash(gmpy.mpq(val,d)))
print("hash tests for rational values passed")
def dnc_nf(p , _G , zflag=False):
def tip(p):
return max(p.coeffs.keys())
if len(p.coeffs)==1:return p
h,cx = nc_p2zp(p)
r = DExpression(p.Nvar)
Nvar = p.Nvar
G = [p.simplify() for p in _G if p!=0]
HMG = [(p , tip(p)) for p in G]
while True:
m = tip(h)
if m==0:
r.coeffs[m] = mpq(h.coeffs[m] , cx)
break
c_h = h.coeffs[m]
if c_h==0:
del h.coeffs[m]
continue
for (p1,m1) in HMG:
if m<m1:continue
if m==m1:
if zflag:
c_ptip = p1.coeffs[m1]
c_g = gcd(c_ptip , c_h)
if c_g<0:c_g = -c_g
c_h //= c_g
c_ptip //= c_g
for m3 in h.coeffs:h.coeffs[m3] *= c_ptip
for m3 in p1.coeffs:
h.coeffs[m3] = h.coeffs.get(m3,0) - c_h*p1.coeffs[m3]
cx *= c_ptip
else:
ct = mpq((c_h.numerator)*(p1.coeffs[m1].denominator) , (c_h.denominator)*(p1.coeffs[m1].numerator))
assert(ct*p1.coeffs[m1]==c_h),(ct,c_h,p1.coeffs[m1])
h -= p1*ct
assert(h.coeffs.get(m,0)==0),(h.coeffs,m,p1.coeffs,zflag)
break
rem = im_div_with_deg(m , m1 , Nvar)
if rem!=None:
c_ptip = p1.coeffs[m1]
um,vm,udeg,vdeg = rem
if zflag:
c_g = gcd(c_ptip , c_h)
if c_g<0:c_g = -c_g
c_h //= c_g
c_ptip //= c_g
cx *= c_ptip
if c_ptip!=1:
for m3 in h.coeffs:
h.coeffs[m3] *= c_ptip
for (m2,c2) in p1.coeffs.items():
deg2 = ideg(m2 , Nvar)
pu,pc,pv = Nvar**udeg,Nvar**deg2,Nvar**vdeg
m3 = pv*(m2-(pc-1)//(Nvar-1))+(vm-(pv-1)//(Nvar-1))
m3 = (pu*pc*pv-1)//(Nvar-1) + (pc*pv)*(um-(pu-1)//(Nvar-1)) + m3
c4 = h.coeffs.get(m3,0) - c_h*c2
if c4!=0 or m3==0:
h.coeffs[m3] = c4
elif m3 in h.coeffs:
del h.coeffs[m3]
else:
for (m2,c2) in p1.coeffs.items():
deg2 = ideg(m2 , Nvar)
pu,pc,pv = Nvar**udeg,Nvar**deg2,Nvar**vdeg
m3 = pv*(m2-(pc-1)//(Nvar-1))+(vm-(pv-1)//(Nvar-1))
m3 = (pu*pc*pv-1)//(Nvar-1) + (pc*pv)*(um-(pu-1)//(Nvar-1)) + m3
#assert(m3==im_mul(um , im_mul(m2, vm,Nvar) , Nvar)),(m2,um,vm,m3)
ct = mpq(c_h*c2 , c_ptip)
c4 = h.coeffs.get(m3,0) - ct
assert(ct*c_ptip==c_h*c2)
if c4!=0 or m3==0:
h.coeffs[m3] = c4
elif m3 in h.coeffs:
del h.coeffs[m3]
#assert(im_mul(um , im_mul(m1,vm,Nvar),Nvar)==m)
#assert(tip(h)<m),(tip(h),m)
break
else:
del h.coeffs[m]
r.coeffs[m] = mpq(c_h,cx)
r.coeffs = dict([(k,Fraction(int(v.numerator),int(v.denominator))) for (k,v) in r.coeffs.items()])
return r
def __rmul__(rhs,lhs):
if isinstance(lhs,DExpression):
return (lhs*rhs)
elif isinstance(lhs,(Number,type(mpz(0)),type(mpq(0,1)))):
return (rhs*lhs)
def __div__(lhs,rhs):
if isinstance(rhs,(Number,type(mpz(0)),type(mpq(0,1)))):
return lhs*Fraction(1,rhs)
else:
assert(False),("invalid division {0}/{1}".format(str(lhs),str(rhs)))
def __rsub__(rhs,lhs):
if isinstance(lhs,DExpression):
return (lhs-rhs)
elif isinstance(lhs,(Number,type(mpz(0)),type(mpq(0,1)))):
return (-rhs+lhs)
def mp2py(r):
if isinstance(r,Number):
return r
elif isinstance(r,(type(mpz(0)),type(mpq(0,1)))):
return Fraction(int(r.numerator) , int(r.denominator))
# relies on Tim Peters' "doctest.py" test-driver
r"""
>>> filter(lambda x: not x.startswith('__'), dir(f))
['as_integer_ratio', 'as_mantissa_exp', 'as_simple_fraction', 'conjugate', 'digits', 'imag', 'is_integer', 'precision', 'rc', 'real']
>>>
"""
try:
import decimal as _d
except ImportError:
_d = None
import gmpy2 as _g, doctest, sys
__test__ = {}
f = _g.mpfr("123.456")
q = _g.mpq("789123/1000")
z = _g.mpz("234")
if _d:
d = _d.Decimal("12.34")
__test__[
"elemop"
] = r"""
>>> print _g.mpz(23) == _d.Decimal(23)
True
>>> print _g.mpz(d)
12
>>> print _g.mpq(d)
617/50
>>> print _g.mpfr(d)
12.34
def dp_nf(p , G , zflag=False):
if not zflag and cgb!=None:
h,c0 = p2zp(p)
r_coeffs,r_weights = cgb.cx_dp_nf(h , G)
r = DPolynomial(p.Nvar , p.Nweight , p.weightMat)
r.coeffs = r_coeffs
r.weights = r_weights
r.coeffs = dict([(k,Fraction(int(val.numerator),int(val.denominator*c0))) for (k,val) in r_coeffs.items()])
return r
def tdeg(p):
return max([sum(m) for m in p.coeffs.keys()])
h,c0 = p2zp(p)
Nweight = p.Nweight
r = DPolynomial(h.Nvar , h.Nweight , h.weightMat)
HMG = [(p.normalize() , p.tip , tdeg(p)) for p in G if p!=0]
if h==0:return r
while True:
h._tip = None
m = h.tip
if len(h.coeffs)==0:break
c_h = h.coeffs[m]
if c_h==0:
del h.coeffs[m]
del h.weights[m]
continue
deg_m = sum(m)
if deg_m==0:
r.coeffs[m] = c_h
r.weights[m] = h.weights[m]
break
for (p1,m1,tdeg1) in HMG:
if tdeg1>deg_m:continue
rem = idiv(m,m1)
if rem==None:continue
w_rem = isub(h.weights[m] , p1.weights[m1])
c1 = p1.coeffs[m1]
if zflag:
c_g = gcd(c1 , c_h)
if c_g<0:c_g = -c_g
c_h //= c_g
c1 //= c_g
if c1!=1:
for m3 in h.coeffs:
h.coeffs[m3] *= c1
for (m2,c2) in p1.coeffs.items():
m3 = iadd(rem , m2)
c4 = (c2*c_h)
if not m3 in h.weights:
h.weights[m3] = iadd(p1.weights[m2] , w_rem)
h.coeffs[m3] = -c4
elif h.coeffs[m3]==c4:
del h.coeffs[m3]
del h.weights[m3]
else:
h.coeffs[m3] = h.coeffs[m3] - c4
if c1!=1:
for m3 in r.coeffs:
r.coeffs[m3] *= c1
else: #-- inefficient
mx = DPolynomial(h.Nvar , h.Nweight , h.weightMat)
cx = mpq(c_h.numerator*c1.denominator,c1.numerator*c_h.denominator)
assert(c1*cx==c_h)
mx.coeffs[rem] = cx
mx.weights[rem] = w_rem
h = h - mx*p1
break
else:
del h.coeffs[m]
r.weights[m] = h.weights[m]
del h.weights[m]
r.coeffs[m] = c_h
r.coeffs = dict([(k,Fraction(int(val.numerator),int(val.denominator))) for (k,val) in r.coeffs.items()])
return r
# partial unit test for gmpy/decimal interoperability
# relies on Tim Peters' "doctest.py" test-driver
r'''
>>> dir(f)
['__abs__', '__add__', '__bool__', '__ceil__', '__class__', '__delattr__', '__divmod__', '__doc__', '__eq__', '__float__', '__floor__', '__floordiv__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__int__', '__le__', '__lt__', '__mod__', '__mul__', '__ne__', '__neg__', '__new__', '__pos__', '__pow__', '__radd__', '__rdivmod__', '__reduce__', '__reduce_ex__', '__repr__', '__rfloordiv__', '__rmod__', '__rmul__', '__rpow__', '__rsub__', '__rtruediv__', '__setattr__', '__sizeof__', '__str__', '__sub__', '__subclasshook__', '__truediv__', '__trunc__', 'binary', 'conjugate', 'digits', 'imag', 'is_inf', 'is_integer', 'is_lessgreater', 'is_nan', 'is_number', 'is_regular', 'is_signed', 'is_unordered', 'is_zero', 'precision', 'rc', 'real']
>>>
'''
try: import decimal as _d
except ImportError: _d = None
import gmpy2 as _g, doctest, sys
__test__={}
f=_g.mpfr('123.456')
q=_g.mpq('789123/1000')
z=_g.mpz('234')
if _d:
d=_d.Decimal('12.34')
fd=_d.Decimal('123.456')
qd=_d.Decimal('789.123')
zd=_d.Decimal('234')
__test__['compat']=\
r'''
>>> f == fd
True
>>> fd == f
True
>>> q == qd
True
>>> qd == q
True
except ImportError as ex:
if ENV_USE_GMPY is True:
raise PysmtImportError(str(ex))
if ENV_USE_GMPY is False:
# Explicitely disable GMPY
USE_GMPY = False
elif ENV_USE_GMPY is True:
# Explicitely enable GMPY
USE_GMPY = True
else:
# Enable GMPY if they are available
USE_GMPY = HAS_GMPY
if HAS_GMPY:
mpq_type = type(mpq(1, 2))
mpz_type = type(mpz(1))
else:
mpq_type = None
mpz_type = None
#
# Fractions using GMPY2
#
from fractions import Fraction as pyFraction
if USE_GMPY:
Fraction = mpq
else:
Fraction = pyFraction
def mpq_from_mpf(value):
if hasattr(value, 'as_integer_ratio'):
return mpq(*value.as_integer_ratio())
raise NotImplementedError
